1 Introduction
2 Impacts of Trade: New Insights from Recent Research
2.1 Taking a Consumption-Based Perspective: What Are Impacts Embodied in Trade?
Impact | Fraction of total global impact embodied in trade (absolute amount, year) | Largest exporter (i), largest importer (ii), largest bilateral trade flow (iii), gross flows, not net flowsa
| Method (name of database/model) | References |
---|---|---|---|---|
CO2 embodied in traded products | (a) 23 % (6.2 Gt CO2, 2004) | (a) (i) China (1.43 Gt CO2) | (a) MRIO analysis (GTAP) | (a) Davis and Caldeira (2010) |
(ii) USA (1.22 Gt CO2) | ||||
(iii) From China to USA (395 Mt CO2) | ||||
(b) 23 % (6.4 Gt CO2, 2004) | (b) (i) China (1.24 Gt CO2, 2004) | (b) MRIO analysis (GTAP) | (b) Davis et al. (2011) | |
(ii) USA (1.22 Gt CO2) | ||||
(c) 22 % (1.7 Gt C = 6.1 Gt CO2, 2004) | (c) n.p.b
| (c) Synthesis of MRIO-based studies | (c) Peters et al. (2012) | |
(d) 25 % (7.5 Gt CO2, 2006) | (d) (iii) From Canada to USA (195 Mt CO2) | (d) EEBTc analysis with life cycle inventory factors for carbon intensity of products | (d) Sato (2014) | |
(e) n.p. (6.9 GtCO2, 2007) | (e) n.p. | (e) MRIO analysis (GTAP) | (e) Andrew et al. (2013) | |
(f) 33 % (8.3 Gt CO2, 2007) | (f) n.p. | (f) MRIO analysis (WIOD) | (f) Xu and Dietzenbacher (2014) | |
(g) 26 % (7.8 Gt CO2 in 2008) | (g) (iii) From China to USA (207 Mt CO2, average 1998–2008) | (g) MRIO analysis (GTAP) using MRIO (global supply chains) and EEBT (domestic supply chains) balances | (g) Peters et al. (2011) | |
CO2 emissions embodied in investments |
n.p.
| (i) Greater China (2.3 Gt CO2, 2004) | Global Interregional Social Accounting Matrix (GTAP) | Bergmann (2013) |
(ii) Western Europe (3.6 Gt CO2, 2004) | ||||
CO2 emissions from traded fossil fuels | (a) 37 % (10.2 Gt CO2, 2004) | (a) (i) Russia (1.47 Gt CO2, 2004) | (a) MRIO analysis (GTAP) | (a) Davis et al. (2011) |
(ii) USA (2.08 Gt CO2) | ||||
(b) n.p. (10.8 Gt CO2 in 2007) | (b) n.p. | b) MRIO analysis (GTAP) | b) Andrew et al. (2013) | |
GHG emissions (CO2, CH4, N2O) | (a) 23 % (8.7 Gt CO2e, 2007) | (a) (iii) From Asia to EU (0.79 Gt CO2e) | (a) MRIO analysis (EXIOBASE) | (a) Tukker et al. (2014) |
(b) 27 % (10.4 Gt CO2e, 2008) | (b) (i) China (2.9 Gt CO2e) | (b) MRIO analysis (WIOD) | (b) Arto et al. (2012) | |
(ii) USA (1.8 Gt CO2e) | ||||
Water | (a) 26 % (2,320 Gm3, 1996–2005) | (a) (i) USA (314 Gm3∕y) | (a) Water Footprint Network method (Hoekstra et al. 2011) | (a) (Hoekstra and Mekonnen (2012); |
(ii) USA (234 Gm3∕y) | ||||
(iii) From USA to Mexico | ||||
(b) 24 % (1900 Gm3, 2000) | (b) (i) USA (180 Gm3) | (b) MRIO analysis (Eora) | (b) Lenzen et al. (2013) | |
(ii) USA (300 Gm3) | ||||
(iii) From USA to Mexico (34.2 Gm3) | ||||
(c) 30 % (2004) | (c) (i) China (204 Gm3) | (c) MRIO (GTAP) | (c) Chen and Chen (2013) | |
(ii) USA (178 Gm3) | ||||
(d) 22 % (2651 Gm3, 2008) | (d) (i) China (472 Gm3) | (d) MRIO analysis (WIOD) | (d) Arto et al. (2012) | |
(ii) USA (427 Gm3) | ||||
Scarce water | (32 % (480 Gm3, 2000) | (i) India (30 Gm3), | MRIO analysis (Eora) | Lenzen et al. (2013) |
(ii) USA (45 Gm3) | ||||
(iii) From Pakistan to USA (7.9 Gm3) | ||||
Land | (a) 24 % (1800 Mgha, 2004) (biologically productive land area) | (a)( i) China (218 Mgha) | (a) MRIO analysis (GTAP) | (a) Weinzettel et al. (2013) |
(ii) USA (326 Mgha) | ||||
(iii) From China to USA (59 mgha) | ||||
(b) n.p.
| (b) (i) Russia (258 Mha) | (b) MRIO analysis (GTAP) | (b) Yu et al. (2013) | |
(ii) USA (198 Mha) | ||||
(iii) From Russia to China (64 Mha) | ||||
(c) 23 % (1660 Mha, 2008) | (c) (i) China (160 Mha) | (c) MRIO analysis (WIOD) | (c) Arto et al. (2012) | |
(ii) USA (260 Mha) | ||||
Cropland |
20 % (271 Mha, 2008) | (i) USA (37 Mha, 2009) | Analysis of bilateral trade data (FAOSTAT) | Kastner et al. (2014a) |
(ii) China (34 Mha, 2009) (MRIO analysis suggests that China is a major exporter Kastner et al., (2014b)) | ||||
(iii) North America to East Asia (18 Mha) | ||||
Threatened species |
30 % (7500 species threats, 2009) | (i) Indonesia (238 species threats) | MRIO analysis (Eora) | Lenzen et al. (2012) |
(ii) USA (1262) | ||||
(iii) Papua New Guinea to Japan (91) | ||||
Energy |
35 % (n.p., 2007) | (i) Russia (23 PJ) | MRIO analysis (EXIOBASE) | Simas et al. (2015) |
(ii) USA (25 PJ) | ||||
Raw materials | (a) 26 % (15 Gt, 2005) | (a) n.p. for countries | (a) IOT and bilateral trade analysis (GRAM/OECD) | (a) Bruckner et al. (2012) |
(i) OECD LD (5.5 Gt) | ||||
(ii) OECD HD (9.9 Gt) | ||||
(b) 34 % (22 Gt, 2007) | (b)( i) China (3.9 Gt) | (b) MRIO analysis (GTAP, materialflows.net) | (b) Giljum et al. (2014) | |
(ii) USA (3.5 Gt) | ||||
(c) 24 % (16 Gt, 2008) | (c) (i) China (2.6 Gt) | (c) MRIO analysis (WIOD) | (c) Arto et al. (2012) | |
(ii) USA (2.8 Gt) | ||||
(d) 41 % (29 Gt, 2008) | (d) (i) India (0.5 Gt biomass) | (d) MRIO analysis (Eora) | (d) Wiedmann et al. (2015) | |
China (5.2 Gt construction materials) | ||||
Russia (1.2 Gt fossil fuels) | ||||
Chile (0.7 Gt metal ores) | ||||
(ii) USA (0.8 Gt biomass | ||||
USA (2.1 Gt construction materials) | ||||
USA (1.3 Gt fossil fuels) | ||||
USA (0.7 Gt metal ores) | ||||
Metal ores |
62 % for iron ore (1,380 Mt, 2008) | (i) Brazil (315 Mt iron ore), Australia (44 Mt bauxite) | MRIO analysis (Eora) | Wiedmann et al. (2014) |
64 % for bauxite (136 Mt, 2008) | (ii) China (350 Mt iron ore), USA (24 Mt bauxite) | |||
Ozone precursors emissions (NMVOC, CH4, CO, NOx) |
28 % (109 Mt NMVOCe, 2008) | (i) China (17.4 Mt NMVOCe) | MRIO analysis (WIOD) | Arto et al. (2012) |
(ii) USA (18.6 Mt NMVOCe) | ||||
Acid emissions (NH3, NOx, SOx) |
26 % (2.1 Mt H+e, 2008) | (i) China (0.65 Mt H+e) | MRIO analysis (WIOD) | Arto et al. (2012) |
(ii) USA (0.35 Mt H+e) | ||||
(a) Labour | (a) 18 % (560 million persons-year equivalents, 2007) | (a) (i) China (130 mpeq) | (a) MRIO analysis (EXIOBASE) | (a) Simas et al. (2015) |
(ii) USA (115 mpeq) | ||||
(iii) China to USA (27 mFTE, 2010, Alsamawi et al. (2014a)) | ||||
(b) ‘Bad’ labour | (b) 16 % for total labour, 15 % for low-skilled labour, 17 % for forced labour, 18 % for occupational health damage, 19 % for child labour,
19 % for vulnerable employment, 20 % for hazardous child labour and 38 % for labour by women (all numbers for trade between seven world regions) | (b) (i) The APAC region is the largest exporter of all forms of (bad) labour, except for child labour and hazardous child labour for which Africa is the largest exporter | (b) MRIO analysis (EXIOBASE) | (b) Simas et al. (2014) |
(ii) n.p. | ||||
(iii) APAC to Europe for all forms of (bad) labour, except for child labour and hazardous child labour for which Africa to Europe is the largest flow | ||||
Wages |
n.p.
| (iii) USA to Japan (112 US$bn, 2010) | MRIO analysis (Eora) | Alsamawi et al. (2014a) |
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Territorial impacts
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+ impacts embodied in imports
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− impacts embodied in exports
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= national footprint
2.2 Recent Research on Environmental, Social and Economic Impacts Embodied in International Trade
2.2.1 Scope and Scale of Embodied Impacts
2.2.2 Trends of Impacts Embodied in Trade
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Land for the export production of crops grew rapidly by +2.1 % per year between 1986 and 2009 (Kastner et al. 2014a). At the same time, land supplying crops for direct domestic use remained almost unchanged.
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Global trade in embodied iron ore has grown faster than its extraction, by a factor of 2.7 between 1990 and 2008 (Wiedmann et al. 2014). Trade of embodied bauxite has grown by a factor of 2.4.
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From 1995 to 2007 total global CO2 emissions from production have increased by 32 %, whereas global emissions embodied in trade have increased by 80 % in the same period (from 4.6 Gt or 24 % of global production emissions to 8.3 Gt or 33 %) (Xu and Dietzenbacher 2014).
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In the most comprehensive study, Arto et al. 2012 present the trend of impacts embodied in trade from 1995 to 2008 for the following indicators: land +3.0 Mkm2 (+22 %); raw materials +7.3 Gt (+80 %); blue, green and grey water +1.2 PL (+88 %); acid emissions +734 kt H+e (+54 %); GHG emissions +4.7 Gt CO2e (+83 %); and ozone precursors emissions +55.3 Mt NMVOCe (+103 %).